Systems and methods for  mediation using nlp and machine learning techniques

ABSTRACT

A system described herein may provide techniques for using machine learning and/or other techniques to monitor a conversation between two or more conversation participants through a messaging program. The system may utilize natural language processing (“NLP”) to determine the intent of phrases and/or words sent between mediation participants. The system may determine to take remedial measures, such as modifying, delaying, and/or rejecting a message from one of the participants when a score for the message exceeds a dynamic score threshold determined by the system based on one or more factors, such as the demographic information of the mediation participants, nature of the mediation, length of mediation, communications among mediation participants, and/or other factors.

BACKGROUND

Devices, such as mobile telephones, tablet computers, etc. offer optionsfor users to message each other. Some users may wish to engage inmediation sessions, in which participants are able to resolve issuesunder the guidance of a trained mediator.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B illustrate an example application of the intelligentmediation message system (“IMMS”), depicted, respectively, from theperspective of the sending participant and the receiving participant, inwhich the IMMS detects a message exceeding a message score threshold andsuggests modifications to the message;

FIG. 2 illustrates an example application of the IMMS in which the IMMSdetects a message exceeding the message score threshold and delays themessage;

FIG. 3 illustrates an example application of the IMMS in which the IMMSdetects a message exceeding the message score threshold and rejects themessage;

FIG. 4 illustrates an example application of the IMMS in which the IMMSinteracts with a user in order to guide the user to modify a messagethat exceeds a message score;

FIGS. 5A and 5B illustrate the ability for the IMMS to handle similarphrases and/or words differently based on conversation context;

FIG. 6 illustrates an example application of the IMMS in which the IMMSdetects a message exceeding the message score threshold and suggestsmediator intervention;

FIG. 7 illustrates an example environment in which one or moreembodiments, described herein, may be implemented;

FIG. 8 illustrates an example process for scoring reference language, inaccordance with some embodiments;

FIG. 9 illustrates an example process for processing a received message,in accordance with some embodiments;

FIG. 10 illustrates an example process for remediating a message bymodification, in accordance with some embodiments;

FIG. 11 illustrates an example process for remediating a message bydelay, in accordance with some embodiments;

FIG. 12 illustrates an example process for remediating a message byrejection, in accordance with some embodiments; and

FIG. 13 illustrates example components of one or more devices, accordingto one or more embodiments described herein.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements.

Mediation provides an avenue for a guided resolution between variousparticipants. However, conventional in-person mediation services may beinconvenient and be prohibitively expensive. As described herein, anIMMS provides a convenient and more affordable avenue for mediation tooccur by allowing participants to use a user equipment (“UE”)—such ascomputer, mobile telephone, and/or other device capable of sending andreceiving communication—to participate in a mediated conversation attheir convenience. However, in many instances, involving a humanmediator in the mediated conversation may be slow and costly (e.g., mayrequire the constant supervision of a mediator). Embodiments describedherein may use machine learning and/or other techniques to analyzemessages to detect improper messages and, if necessary, take remedialmeasures. For instance, as described below, the IMMS may detect amessage which may be deemed offensive, unproductive, ambiguous, and/orotherwise in need of remediation, and may suggest message modifications,reject the message, delay the message, and/or perform other remedialmeasures.

As shown in FIG. 1A, for example, user interface 100 may depict aconversation between two example participants (“P1” and “P2”) in amediation session, in accordance with some embodiments. As describedherein, the mediation session may be administered by the IMMS (e.g., theIMMS may detect messages that may need remediation, and may performdifferent remediation measures based on the content of the messages, theoverall intent of the conversation, the relationship between the twoparties, and/or other factors). As shown, for example, user P1 may senda message saying “Dude, you're being dramatic.” In some embodiments, theIMMS may determine that this message exceeds a message score threshold(e.g., a threshold indicating that the message should be remediated). Asdescribed below, the message score threshold may be modified by variousfactors, including, but not limited to, the frequency of messages, theoverall conversation intent (or “temperature”), the content or intent ofthe message, and/or specific characteristics of the mediationparticipants. Here, for example, the message may exceed the messagescore threshold based on the content of the message, rather than a highmessage score threshold. As shown, the IMMS may analyze the message andtake an appropriate remedial measure. For example, in this instance, theIMMS recommends alternative language for the message. As describedbelow, the IMMS may determine substitute phrases and/or words by usingnatural language processing (“NLP”) and/or other suitable techniques todetermine a syntactical meaning or intent of the message, and may usemachine learning and/or other suitable techniques to determine phrasesand/or words having a similar meaning, but in a more appropriate manner(e.g., where a message score for the replacement message does not exceedthe message score threshold). The IMMS may recommend replacementlanguage to the sending participant and request approval from thesending participant.

For instance, as shown in FIG. 1A, the IMMS may intercept the messageprior to the message being sent to P2 and may prevent the interceptedmessage from being sent to P2. In some embodiments, the IMMS maypresent, via user interface 100, notification message 105, indicatingthat the message was not sent. The IMMS may also present, via userinterface 100, arrow 110 between the message and notification message105. Arrow 110 may indicate that notification message 105 is related tothe triggering message (e.g., the message which exceeded the messagescore threshold), and may also be used to indicate that the triggeringmessage was not sent. The IMMS may also use other types of indicators(e.g., a notification popup, message quote, a different font, such as anitalicized or struck through font, different size, bolding, a differenttypeface, color, or the like) to indicate that a message has not beensent to the other user P2. In this figure, for example, italics are usedfor messages that are not sent to P2, while non-italic fonts are usedfor messages that are sent between users P1 and P2.

Additionally, notification message 105 may include a prompt (“do youaccept the suggested edits below?”), asking if the user accepts areplacement for the message (indicated in suggestion message 115). Asshown, suggestion message 115 may include a replacement for the originalmessage. As described herein, the IMMS may have generated thereplacement message by using NLP and/or other suitable techniques todetermine an intent and/or meaning of the original message (e.g., in thecontext of one or more other messages, in some embodiments, where thecontext of multiple different messages may have an effect on the intentor meaning of the original message). In some embodiments, the IMMS mayuse machine learning and/or other suitable techniques to determine thereplacement message. For example, the IMMS may maintain informationindicating that the phrase “might be overstating the consequences of myactions” has been viewed favorably by mediation participants (e.g., incomparison to other candidate phrases, and/or in comparison to thephrase “you're being dramatic”). For instance, the IMMS (and/or someother system) may have determined that past recipients of thereplacement phrase have responded with messages that have a morefavorable or amicable intent (e.g., as determined through NLP or othersuitable techniques) than the original phrase.

As further shown, P1 may affirmatively respond (via message 120) to theprompt. Because the IMMS previously sent a prompt (e.g., via messages105 and 115), the IMMS may be able to use NLP and/or other suitabletechniques to determine that a message from the user is a response tothe prompt (e.g., an affirmative response such as “yes,” “yeah,”“definitely,” etc., even if these responses are not pre-configured to berecognized by the IMMS).

Once the affirmative response is received by the IMMS, the IMMS may sendmessage 125 on behalf of user P1. That is, from the standpoint of userP2, it may be indistinguishable which messages were typed by user P1 andwhich messages were provided/edited by the IMMS. For instance, as shownin FIG. 1B, user interface 150 (e.g., as displayed on a UE associatedwith user P2) may not receive or present any of messages 105-120.Further, user interface 150 may present message 125 as though it wassent by the IMMS on behalf of P1. As demonstrated in FIGS. 1A and 1B,message 125 may be presented in the font format indicating a sentmessage (e.g., in this instance, non-italic font) on user interfaces 100and 150.

The IMMS may, in some embodiments, use message frequency as a factor indetermining whether a given message exceeds a message score threshold.As shown in FIG. 2, for example, user P2 may send a series of messages(e.g., via user interface 200) without a response from user P1. Asdescribed below, the message score threshold may be modified by variousfactors, including, but not limited to, the frequency of messages,response from other participants, a quantity of consecutive messagesfrom one party without a response from the other party, or the like.Here, for example, the message score threshold may be modified as aresult of the high frequency of messages, lack of response from user P1,and message intent (e.g., here, the intent may be seen as insulting). Asfurther depicted here, the triggering message (“It's not worth my time”)may exceed the message score threshold based on the frequency ofmessages and lack of response from user P1, whereas it may not exceedthe message score threshold in other scenarios. In some embodiments, amessage score may be modified (e.g., by a factor or increment) insteadof the message score threshold. For example, as depicted here, themessage score for the triggering message (“It's not worth my time”) maybe modified by a factor as a result of the number of messages sent byuser P2, causing the triggering message to exceed the message scorethreshold. As shown, the IMMS may analyze the message and take anappropriate remedial measure. For example, in this instance, the IMMSdelays the message.

For instance, as shown in FIG. 2, the IMMS may intercept the triggeringmessage prior to being sent to P1 and may prevent the message from beingsent to P1. In some embodiments, the IMMS may present, via userinterface 200, notification message 205, indicating that the message wasnot sent. In some instances, the IMMS may notify the participant why themessage was not sent. For example, here, the IMMS indicates that themessage was delayed because the user sent too many messages in highfrequency. In some embodiments, the IMMS may update notification message205 as time progresses (e.g., simulate a countdown timer by changing thenumber of seconds left before automatically sending the message).

Additionally, notification message 205 may include an indication (“Youcan edit your message before it is automatically sent in 10 seconds”)allowing the participant to modify the message before it is transmitted.In some embodiments, the participant may select the triggering messageand input a new message. In further embodiments, the participant maytype a response indicating the desire to modify the message beforetransmission. In such an embodiment, the IMMS may be able to utilize NLPand/or other suitable techniques to determine that a message from theuser is a response to the indication (e.g., “modify,” “yes,” “change,”etc.). In some embodiments, the IMMS will not automatically send auser-modified message, but instead require the user to resubmit thatmessage (e.g., the IMMS will treat the message as a new message andscore it to determine whether to take a remedial measure). If the userdoes not take an action, the IMMS may send the triggering message onbehalf of user P2. That is, from the standpoint of user P1, the messagemay be indistinguishable that the message was sent by user P2 or theIMMS or that any remedial measure was taken (e.g., as in this instance,that the message was delayed).

In some embodiments, the IMMS may reject a user-submitted message. Asshown in FIG. 3, for example, user P2 may send a message (e.g., via userinterface 300) saying, “I think you're full of it.” As shown, the IMMSmay analyze the message and take an appropriate remedial measure. Here,for example, the IMMS may determine that the message exceeds the messagescore threshold based on the content of the message. In this instance,the IMMS rejects the message and requests user P2 to submit a newmessage (e.g., at message 305).

As further shown, P2 may attempt to submit a new message to the IMMS(via new message 310). This new message may be analyzed by the IMMS todetermine which, if any, remedial measure should be taken. Asdemonstrated here, new message 310 does not exceed a message scorethreshold and is sent to user P1.

In some embodiments, the IMMS may interact with a user in order to guidethe user to modify a message that exceeds a message score threshold. Asshown in FIG. 4, for example, user P2 may submit a message (depicted astriggering message 405 in user interface 400) saying “I think you andyour TPS reports are stupid.” In some embodiments, the IMMS maydetermine that this message exceeds a message score threshold. Here, forexample, the message may exceed the message score threshold based on thecontent of the message. As shown, the IMMS may analyze the message andtake an appropriate remedial measure. For example, in this instance, theIMMS may attempt to clarify ambiguous language, recommend replacementlanguage to the sending participant, and request approval from thesending participant.

For instance, as shown in FIG. 4, the IMMS may intercept triggeringmessage 405 prior to triggering message 405 being sent to P1 and mayprevent triggering message 405 from being sent to P1. In someembodiments, the IMMS may present, via user interface 400, notificationmessage 410, indicating that triggering message 405 was not sent.

As described, the IMMS may display, via user interface 400, a messageasking the user to explain ambiguous language (demonstrated here asnotification message 410, “What is ‘stupid’ about TPS reports?”). Insome embodiments, the IMMS may use machine learning and/or othersuitable techniques to determine whether a phrase and/or word isambiguous. For instance, the IMMS may maintain information thatindicates that when a given message has been sent to users in the past,the receiving participant has responded with a statement indicatingtheir confusion, such as, “I don't know what you mean,” “I'm confused,”“what do you mean,” etc. In some embodiments, the IMMS may use NLPand/or other suitable language recognition techniques to determinewhether a phrase and/or is vague or otherwise unclear (e.g., multipleintents exist and it ambiguous to which is used, and/or the IMMS isunable to determine a meaning or intent of the message). The user maythen provide additional information to clarify the statement (e.g.,demonstrated here as response message 415, “They are a waste of time”).

Additionally, the IMMS may display message 420 with a prompt (“do youaccept the suggested edits below?”), asking if the user accepts amodified message (indicated in suggestion message 425). As shown,suggestion message 425 may include a replacement for the originalmessage and the explained message (e.g., here, the user responseprovided via response message 415). As described herein, the IMMS maygenerate the replacement message by using NLP and/or other suitabletechniques to determine an intent and/or meaning of the originalmessage. In some embodiments, the IMMS may use machine learning and/orother suitable techniques to determine the replacement message. Forexample, the IMMS may maintain information indicating that the phrase“can be more efficient” has previously been viewed favorably bymediation participants (e.g., in comparison to other candidate phrases,and/or in comparison to the phrase “are a waste of time”). For instance,the IMMS (and/or some other system) may have determined that pastrecipients of the replacement phrase have responded with messages thathave a more favorable or amicable intent (e.g., as determined throughNLP and/or other suitable techniques) than the original phrase.Similarly, the IMMS may remove or modify language that is derogatory,negative, or insulting (e.g., as determined through informationmaintained in a language repository or through NLP and/or other suitabletechniques). For instance, the IMMS may remove the phrase “you . . . arestupid” because the phrase may be determined to be derogatory orinsulting (e.g., because it attacks the intelligence of anotherparticipant).

As further shown, P2 may affirmatively respond (via message 430) to theprompt (e.g., message 420). Because the IMMS previously sent a prompt(e.g., via message 420), the IMMS may be able to use NLP and/or othersuitable techniques to determine that a message from the user is aresponse to the prompt. Here, for example, the IMMS recognizes theaffirmative response in message 430 (“Yes”).

Once the affirmative response is received by the IMMS, the IMMS may sendmessage 435 on behalf of user P2. That is, from the standpoint of userP1, it may be indistinguishable which messages were typed by user P1 andwhich messages were provided/edited by the IMMS (e.g., user P1 will seemessage 435 as though P2 sent message 435).

In some embodiments, the IMMS may use NLP and/or other suitabletechniques to determine the intent of a message and, in doing so, maydistinguish between two different uses of the same phrase and/or word.Accordingly, the IMMS may handle the same phrase and/or word indifferent manner based on the determined intent or participantcharacteristics (e.g., participant relationship, demographiccharacteristics, etc.). In FIG. 5A, for example, the IMMS may determinethe intent of a phrase (“Shut up!”, in this example) to be congruous.However, in FIG. 5B, for example, the IMMS may determine the intent ofthe same phrase to be contentious and cause the message score to exceedthe message score threshold. As a separate example, the IMMS maydetermine the use of a phrase (here, “Shut up! ”) to be congruous whenused between close friends (e.g., as depicted in FIG. 5A) butcontentious when used between a supervisor and employee (e.g., asdepicted in FIG. 5B). The IMMS may take an appropriate remedial measureagainst contentious phrases. For example, as depicted in FIG. 5B, theIMMS may reject the message. The relationship of the participants may bedetermined based on information provided by the participants (e.g., oneor more of the participants may indicate their relationship to eachother), and/or the relationship may be determined based on other factors(e.g., participants with a same last name may be inferred to be related;social media accounts associated with the participants may indicate arelationship; etc.).

As shown in FIG. 5B, the IMMS may present (via user interface 550)notification message 505 indicating that the message has not been sentand a prompt (“please try again”) requesting the user to submit a newmessage. As further shown, P2 may respond to the prompt with a newmessage (“I've never been late to work”). The IMMS may analyze the newmessage to determine whether the message exceeds a message scorethreshold and which, if any, remedial measure should be taken. Forexample, in this instance, the new message does not exceed the messagescore threshold and the IMMS takes no remedial measure, allowing the newmessage to be sent to user P1.

In some embodiments, the IMMS may determine hostile intent by thesending participant, reject the message, and recommend mediatorintervention. As shown in FIG. 6, for example, user P2 may submit amessage saying, “You jerk! You wrecked my car! I'm not going to restuntil I own your children's children!” In some embodiments, the IMMS maydetermine that this message exceeds a message score threshold. Here, forexample, the message may exceed the message score threshold based on theintent of the message. The intent of the message may be determined usingNLP and/or other suitable techniques. As shown, the IMMS may analyze themessage and take an appropriate remedial measure. For example, in thisinstance, the IMMS may reject the message and recommend the user consultwith a mediator before continuing (e.g., as depicted in message 605). Insuch instances, the IMMS may intercept future message(s) from thesending participant and prevent the intercepted message(s) from beingsent, subject to approval by a mediator participant.

FIG. 7 illustrates example environment 700 in which one or moreembodiments described herein may be implemented. Environment 700 mayinclude UEs 705 (e.g., UE 705-1, 705-2, and 705-3 (collectively referredto herein as “UEs 705” or individually as “UE 705”)), network 710, IMMS715, scoring component 720, and reference language repository 725.

UEs 705 may include any device capable of sending, receiving, anddisplaying communications such as a computer, mobile telephone, and/orother devices. UE 705-1 may be associated with a mediator (e.g., anyperson or persons independent from the mediation participants who willadvance mediation and/or otherwise intervene in conversations betweenparticipants). UEs 705-2 and 705-3 may be associated with at least twoparticipants. In some embodiments, IMMS 715 may administer a mediationamong more than two participants or allow multiple participant UEs forthe same side of the mediation (e.g., to allow an insurance carrier andthe insured party to participate in mediation opposing the plaintiff).UEs 710 may display user interfaces in accordance with some embodimentsdescribed herein. For example, UEs 705 may display user interfaces 100,150, 200, 300, 400, 500, 550, and 600, where appropriate (e.g., per thelimitations of which mediation participant receives which message).

FIG. 7 further depicts IMMS 715. IMMS 715 may contain one or morecomponents, including, for example, scoring component 720 and/orreference language repository 725. IMMS 715 may administer a mediationbetween participants. As such, IMMS 715 may intercept and analyze sentmessages to determine which, if any, remedial measures should be taken.In doing so, IMMS 715 may rely on one or more components, including, forexample, scoring component 720 and reference language repository 725.

Scoring component 720 may determine a message score threshold as well asthe individual message score for a particular message. As describedbelow, the message score threshold may be adjusted according to severalfactors, including, but not limited to, the frequency of messages, themediation temperature, the content of the message, and/or specificcharacteristics of the mediation participants. As further describedbelow, the message score may be determined by the content of the message(e.g., including any contentious, congruous, or mitigating phrasesand/or words) or message intent. Message intent may be determined usingNLP and/or other suitable method to determine the intent of the phrasesand/or words being used. For example, IMMS 715 may use NLP lexicalsemantic techniques to determine the contextual meaning of words.

Reference language repository 725 may be a database or other structureddata storage repository designed to store information. In someembodiments, reference language repository 725 may include the referencephrase and/or word in addition to a score, alternative phrases and/orwords, intent, and/or other information related to potential use for thephrase and/or word (e.g., syntactic role, common misspellings, etc.).Reference language repository 725 may additionally link related phrasesand/or words (e.g., words with similar definitions, commonly misusedwords, and their proper counterparts, etc.).

Devices in environment 700 may communicate through network 710. Network710 may include any network infrastructure, including wirelesstelecommunication networks (e.g., Fourth Generation (4G), FifthGeneration (5G) infrastructure, etc.), wired internet networks, localarea networks, and/or other network systems which permit communication.Devices of environment 700 may interconnect with each other and/or otherdevices via wired connections, wireless connections, or a combination ofwired and wireless connections.

The quantity of devices and/or networks, illustrated in FIG. 7, isprovided for explanatory purposes only. In practice, environment 700 mayinclude additional devices and/or networks; fewer devices and/ornetworks; different devices and/or networks; or differently arrangeddevices and/or networks than illustrated in FIG. 7. For example, asdescribed above, in some embodiments there may be additional UEs 705.Alternatively, or additionally, one or more of the devices ofenvironment 700 may perform one or more functions described as beingperformed by another one or more of the devices of environments 700. Forexample, UEs 705 may perform some functions of IMMS 715, such asanalyzing or intercepting messages. In some implementations, one or moredevices of environment 700 may be implemented by, be physicallyintegrated in, and/or may be communicatively coupled with, one or moreother devices of environment 700. For example, while IMMS 715 isdisplayed as a separate device, some or all of the functionality of IMMS715 may be implemented by one or more devices (e.g., within UEs 705and/or another device).

FIG. 8 illustrates a process 800 for scoring and storing or outputtingphrases and/or words. In some embodiments, all or some of the processmay be performed by scoring component 720 and/or by one or more devicesand/or systems.

As shown, process 800 may include receiving and/or identifying (at 805)reference phrases and/or words. Reference phrases and/or words may beprovided by IMMS 715 and/or one or more devices (e.g., referencelanguage repository 725 or UEs 705, etc.). Identifying may consist ofparsing (e.g., for example, using NLP techniques) phrases and/or wordsto different segments. For example, if scoring component 720 receivesthe message, “I want to take a break,” process scoring component 720 mayidentify phrases such as “I want” or “to take a break” or individualwords such as “break.” Accordingly, each segment may be individuallyanalyzed using process 800.

Process 800 may also include determining (at 810) the intent of thephrase and/or word. The phrase and/or word intent may be determined byusing NLP or other suitable techniques to analyze several factors,including, but not limited to, the context in which the phrase and/orword is used and/or modifiers affecting the phrase and/or word. Thephrase and/or word intent may be pertinent to determine what the phraseand/or word is being used to express in order to properly score thephrase and/or word (e.g., when scoring, at 815) and/or to establish whatsubstitute phrase and/or word may be available (e.g., when identifyingalternative phrases and/or words, at 820). For example, if the systemidentified word, such as “break,” it could be used to express thedestruction of an object or the desire to take a rest.

Process 800 may also include scoring (at 815) the reference phraseand/or word. Scoring may occur, for example, on a score gradientdepending on the intent of the language. For instance, scoring component720 may provide the word “break” a more agreeable score (e.g., congruouslanguage score, suitable language score, etc.) if the word is intendedto describe “taking a rest” but may provide a less agreeable score(e.g., contentious language score, unsuitable language score, etc.) ifthe word is intended to describe “destroying an object.” In someembodiments, if a mediation participant accepts or rejects analternative phrase and/or word (e.g., alternative phrase and/or worddetermined at 820, used at 1040, for example), the suggested alternativephrase and/or word may be scored more or less agreeable, respectively,than the original phrase and/or word. For example, if a mediationparticipant accepts an alternative phrase of “take an intermission” toreplace “take a break,” the alternative phrase would receive a moreagreeable (e.g., more suitable) score than the original phrase.Similarly, for example, if a mediation participant rejects the phrase“take time off” to replace “take a break,” the alternative phrase wouldreceive a less agreeable (e.g., less suitable) score than the originalphrase.

Process 800 may also include identifying (at 820) alternative phrasesand/or words. The alternative phrase and/or word may be identifiedthrough phrases and/or words of related intent (which may be determinedthrough NLP and/or other suitable techniques). In some embodiments, whencombined with a score (e.g., from 815), identifying (at 820) alternativephrases and/or words may allow the ability to compare related phrasesand/or words with other related phrases and/or words with differentscores. For example, the word “break,” with the intent to describe“rest,” may be associated with another word such as “intermission”(e.g., more suitable score, etc.), and/or a phrase such as “time off”(e.g., less suitable score, etc.). Process 800 may use NLP and/or othersuitable techniques to contextually determine the intent of a phraseand/or word even if not configured to determine the intent throughdefinition. For example, if scoring component 720 receives the phrase,“that's pretty fly,” scoring component 720 may determine from contextthat the phrase means “cool.”

Process 800 may also include outputting and/or storing (at 825) thereference phrase and/or word. For example, if process 800 is initiatedby a determination to modify a message (e.g., from 945), the referencelanguage may be output (e.g., to IMMS 715) and/or stored (e.g., inreference language repository 725). As an additional example, if process800 is initiated by creating and/or updating reference languagerepository 725, the reference language may be stored (e.g., in referencelanguage repository 725).

In some embodiments, the reference phrase and/or word may be outputand/or stored along with the intent, identified alternative phrasesand/or words (e.g., from 820) and correlating scores, a score (e.g.,from 815), intent (e.g., from 810), and/or other information related topotential use for the phrase and/or word (e.g., syntactic role, commonmisspellings, etc.). For example, the word “break” may be output (orstored) with identified (e.g., from 820) alternative phrases and/orwords with matching intent (e.g., “intermission,” “rest,” “time off,”etc.) and correlating scores for alternative phrases and/or.

FIG. 9 illustrates a process 900 for determining whether to take aremedial measure after receiving a message. In some embodiments, all orsome of the process may be performed by IMMS 715 and/or by one or moredevices and/or systems.

As shown, process 900 may include receiving (at 905) mediationinformation, which may include information regarding the participants(e.g., participant names, gender, nationality, age, relationship toother participants, and/or other demographic information about theparticipants, etc.) but may also include information regarding themediation (e.g., information regarding the nature of the dispute, thelength of the dispute, previous communications between the parties,and/or relevant evidence regarding the dispute, etc.) and/or otherrelevant information regarding the mediation (e.g., applicable laws,evidence, etc.).

Process 900 may also include identifying (at 910) relevant participantcharacteristics. Characteristics may include demographic informationsuch as age, disposition, and relationships between participants, butalso include statistical information, such as likeliness to preferformal language, likeliness for dispositions towards gender ornationality, and/or other relevant characteristic traits. For example,IMMS 715 might receive (e.g., at 905) demographic information for amediation wherein one of the participants is an older male. Thisdemographic information may statistically suggest, for example, that theparticipant prefers being spoken to in more formal language. As such,IMMS 715 may identify (at 910) a desire for formal language as arelevant participant characteristic.

Process 900 may also include receiving (at 915) a message from thesending participant. The message may be in any data format such as shortmessage service, multimedia messaging service, internet protocol-basedmessaging and/or other text-based messaging architecture.

Process 900 may include aggregating and/or determining (at 920) themediation temperature level. The mediation temperature level may be anaggregate of various factors related to the ongoing mediation such as,the relationship between the participants (e.g., neighbors, parent andchild, etc.), previous disputes between the participants, messages sentbetween the participants (e.g., messages sent during or precedingmediation), individual characteristics of the participants (e.g., aparticipant is “hot-headed,” prefers formal language, or is easilyinsulted, etc.) and other relevant characteristics identified (e.g.,from 910), and/or the nature of the incident arising to the particularmediation, etc. As the mediation continues, process 900 may continuouslymodify the mediation temperature level in accordance with consideredfactors. For example, IMMS 715 may aggregate an initially mild (e.g.,low) mediation temperature between a parent and child. As provocativewords are shared between the participants, IMMS 715 may aggregate aharsh (e.g., high) mediation temperature. Similarly, a harsh mediationtemperature level may be moderated (e.g., lowered) as participants sendplacatory messages.

Process 900 may also include determining (at 925) a message scorethreshold. The message score threshold may be adjusted according toseveral factors, including, but not limited to, the frequency ofmessages, the mediation temperature level (e.g., from 920), the contentof the message, and/or mediation information (e.g., from 905) includingspecific characteristics of the mediation participants. In someembodiments IMMS 715 may establish several message score thresholds ofdifferent magnitude corresponding with different remedial measures.These may be used in determining (e.g., at 945) which remedial measureto take (e.g., exceeding a more severe score threshold would beassociated with a more severe remedial measure).

Process 900 may also include calculating (at 930) the score for thereceived message. The message score may be determined, for example, bypassing the message through process 800. As discussed above, scoring themessage may include segmenting the message into various phrases and/orwords and processing each segment individually. Each segment containingphrases and/or words may be scored based on the intent, modifyingdescriptors (e.g., adjectives, adverbs, etc.), and/or other factorswhich can be used to determine the suitability of the segment. Themessage score may consider the aggregate of the various segments ofphrases and/or words (e.g., each segment of the entire message).

Process 900 may include a determination (at 935) of whether the messagescore exceeds a score threshold. For example, in some embodiments, themessage may be scored through process 800 and compared to the determinedmessage score threshold (e.g., from 925). If the message score exceeds amessage score threshold (at 935—Yes), process 900 may take a remedialmeasure (e.g., at 945). If the message does not exceed a message scorethreshold (at 935—No), process 900 may output the message (e.g., at940).

Process 900 may further include outputting (at 940) the message to UEs705 (e.g., UEs 705 associated with sending participant, receivingparticipant(s) and/or mediator(s)). In some embodiments, process 900 mayoutput the message in any data format such as short message service,multimedia messaging service, internet protocol-based messaging and/orother text-based messaging architecture. The message may be transmittedover network 710. In some embodiments, the receiving participant may bequeried (e.g., through a notification or display on UE 705) regardingwhether the receiving participant perceives the message as suitable(e.g., on a scale of more to less suitable, etc.). The query may beinitiated by a participant (e.g., voluntarily by the receivingparticipant or mandated by the sending participant) or by one or moredevices (e.g., IMMS 715). This query may provide feedback to establishuser-reinforced machine learning for reference language repository 725and/or other data structures.

Process 900 may include taking (at 945) a remedial measure. Remedialmeasures may include modifying the message (e.g., process 1000),delaying the message (e.g., process 1100), and/or rejecting the message(e.g., process 1200). Process 900 may determine which remedial measureto take (at 945) by comparing the message score (e.g., from 930) and themessage score threshold (e.g., from 925) to determine how much in excessthe message score exceeds the message score threshold. In instanceswhere the message score threshold is marginally exceeded by the messagescore, IMMS 715 may take a less severe remedial measure (e.g., delay themessage). In instances where the message score threshold is greatlyexceeded by the message score, IMMS 715 may take a more severe remedialmeasure (e.g., reject the message). In some embodiments, IMMS 715 maymodify the message in any instance where a message score threshold isexceeded by the message score before pursuing other remedial measures.For example, if a message score scarcely exceeds the message scorethreshold, IMMS 715 may modify the message to lower the score beforedelaying the message. In some embodiments, IMMS 715 may use messagescore thresholds of different magnitudes to determine which remedialmeasure to take (e.g., exceeding a more severe score threshold resultsin a more severe remedial measure).

FIG. 10 illustrates a process 1000 for remedying a message throughmodification. In some embodiments, some or all of process 1000 may beperformed by IMMS 715 and/or by one or more other devices or systems. Asdiscussed above, process 1000 may be favored in any instance where themessage score exceeds the message score threshold. Process 1000 isdemonstrated, for example, in FIGS. 1A & 1B and FIG. 4.

As shown, process 1000 may include receiving (at 1005) a message formodification. As discussed above, process 900 may determine (e.g., at945) to modify a message if the message score exceeds a message scorethreshold (e.g., from 935).

Process 1000 may include receiving (at 1010) the message scorethreshold. As discussed above, the message score threshold takes intoconsideration several factors, including, but not limited to, therelationship between the participants (e.g., neighbors, parent/child,etc.), previous disputes between the participants, messages sent betweenthe participants (e.g., messages sent during or preceding mediation),relevant characteristics of the participants (e.g., a participant is“hot-headed” or easily angered, demographic information, dispositions,etc.), and/or the nature of the incident arising to the particularmediation. The message score threshold provides a level, which ifexceeded, may indicate the need to further modify the received message(e.g., from 1005).

Process 1000 may also include identifying (at 1015) messagecharacteristics. This segments the message into pieces of phrases and/orwords which may be modified to increase or lower the message score. Insome embodiments, each segment of phrases and/or words may be scored(e.g., through process 800) to identify segments for modification basedon segment score.

In some embodiments, process 1000 may maintain a repository and/orutilize NLP and/or other suitable techniques to identify phrases and/orwords that are ambiguous or unclear for a determination (at 1020)whether there is ambiguous language present. This determination may bemade based on identified (e.g., from 1015) message characteristics.Ambiguous language may include language that is vague or has multipledefinitions which cannot be distinguished in the context. For example,some phrases, such as “this is stupid,” does not provide a clear contextof the message intent because the word “stupid” may refer to any numberof descriptors (e.g., adverbs, adjectives, etc.) which may moreaccurately express the sending participant's intent.

Process 1000 may include determining (at 1020) whether there isambiguous language present in the message. As discussed above, ambiguouslanguage may include phrases and/or words that are vague or have with noascertainable meaning. In response to detecting ambiguous language (at1020—Yes), process 1000 may query (at 1055) the sending participantregarding the ambiguous language. Process 1000 may output a message tothe sending participant (e.g., notification message 410) to indicate therequest to request to receive an explanatory information. In someembodiments, process 1000 may substitute (at 1060) the ambiguouslanguage with the more defined language provided by the sendingparticipant. The message containing substitute language may undergoparts of process 1000 as the original message (e.g., from 1015-1060).

In response to not detecting (at 1020—No) ambiguous language, process1000 may add, remove, and/or substitute (at 1025) phrase and/or word tomodify the message score. Process 1000 may utilize a data repository(e.g., reference language repository 725) to determine alternativelanguage to add, substitute, and/or replace phrases and/or words in theoriginal message. As discussed above, phrases and/or words may beassociated with a score, but may also include alternative phrases and/orwords with corresponding scores. When modifying the message, process1000 may consider message syntax (e.g., syntax data stored withreference language or determined through NLP and/or other suitableprocesses, etc.) and organize alternative phrases and/or words to begrammatically correct.

Process 1000 may further include scoring (at 1030) the modified message.The modified message score may be determined, for example, by passingthe modified message through process 800. As discussed above, scoringthe modified message may include segmenting the modified message intovarious phrases and/or words and processing each segment individually.Each segment containing phrases and/or words may be scored based on theintent, modifying language (e.g., adjectives, adverbs, etc.), and/orother factors which can be used to determine the suitability of thesegment. The message score may consider the aggregate of the varioussegments of phrases and/or words (e.g., the entire modified message).

Process 1000 may include detecting (at 1035) whether the modifiedmessage score exceeds a message score threshold. IMMS 715 may utilizethe previously obtained message score (e.g., from 1030) or message scorethreshold (e.g., from 1010). In some embodiments, if the modifiedmessage score exceeds the score threshold (at 1035—Yes) process 1000 mayiterate the modification process to further moderate the message score(e.g., repeat process 1000 from 1015-1035).

Upon determining that the modified message score does not exceed thescore threshold (at 1035—No), process 1000 may output (at 1040) themodified message to UE 705 associated with the sending participant forapproval. In some embodiments, process 1000 may output the modifiedmessage in any data format such as short message service, multimediamessaging service, internet protocol-based messaging and/or othertext-based messaging architecture. In some embodiments, the modifiedmessage may be transmitted over network 710. In some embodiments, thesending participant may be queried (e.g., through a notification ordisplay on UE 705) regarding whether the sending participant perceivesthe modified message as suitable (e.g., on a scale of more to lesssuitable, etc., based on the modified phrases and/or words). The querymay be initiated by the sending participant or one or more devices(e.g., IMMS 715). This query may provide feedback to establishuser-reinforced machine learning for reference language repository 725and/or other data structures. In some embodiments, the sendingparticipant may further modify the modified message. In such instances,the received message may be treated as a new message and may besubmitted to process 900.

Process 1000 may further include outputting (at 1045) the modifiedmessage to UEs 705 (e.g., UEs 705 associated with sending participant,receiving participant(s) and/or mediator(s)). In some embodiments,process 1000 may output the modified message in any data format such asshort message service, multimedia messaging service, internetprotocol-based messaging and/or other text-based messaging architecture.In some embodiments, the modified message may be transmitted overnetwork 710. In some embodiments, the receiving participant may bequeried (e.g., through a notification or display on UE 705) regardingwhether the receiving participant perceives the message as suitable(e.g., on a scale of more to less suitable, etc.). The query may beinitiated by a participant (e.g., voluntarily by the receivingparticipant or mandated by the sending participant) or by one or moredevices (e.g., IMMS 715). This query may provide feedback to establishuser-reinforced machine learning for reference language repository 725and/or other data structures.

Process 1000 may include outputting (at 1050) the modified message toprocess 800. As discussed above, process 800 may score, store, and/oroutput reference language. As described above, process 1000 may favoroutputting the modified message to process 800 particularly ifparticipant UE 710 provides an affirmative or negative response to theoutput modified message (e.g., at 1040). Outputting the modified messageto process 800 may, for example, provide feedback to establishuser-reinforced machine learning for reference language repository 725and/or other data structures.

FIG. 11 illustrates a process 1100 for remedying a message throughdelay. In some embodiments, some or all of process 1100 may be performedby IMMS 715 and/or by one or more other devices or systems. As discussedabove, process 1100 may be favored, for example, in instances when amessage score marginally exceeds the message score threshold. Process1100 is demonstrated, for example, in FIG. 2.

As shown, process 1100 may include receiving (at 1105) a message fordelay. As discussed above, IMMS 715 may determine (e.g., at 945) todelay a message if the message score exceeds a message score threshold(e.g., at 935).

Process 1100 may also include querying (at 1110) the sending participantwhether the sending participant wants to modify the message. As shown inFIG. 2 (e.g., at 205), the message may indicate the reason for thedelay. This delay may cause the sending participant to reconsidersending the message.

Process 1100 may further include receiving (at 1115) the query responsefrom sending participant. The response from the sending participant maytake different forms. For example, in some embodiments, the sendingparticipant may be able to directly modify the message as displayed onUE 705 (e.g., modify the message as displayed in user interfaces 100,150, 200, 300, 400, 500, 550, and 600). As a further example, in someembodiments, the sending participant may be able to send a messageindicating the desire to modify the message held for delay. In suchinstances, IMMS 715 may be able to use NLP and/or other suitabletechniques to determine that a message from the user is a response tothe prompt (e.g., an affirmative response such as “yes,” “yeah,”“definitely,” etc., even if these responses are not pre-configured to berecognized by IMMS 715).

Process 1100 may include determining (at 1120) whether the sendingparticipant desires to modify the message. Upon a determination that thesending participant desires to modify the message (at 1120—Yes) process1100 may receive (at 1135) the new or modified message from the sendingparticipant. In that instance, process 1100 may further output (at 1140)the new or modified message received (e.g., from 1135) to process 900.

In instances where process 1100 does not determine (at 1120—No) that thesending participant desires to modify the message, process 1100 mayinclude delaying (at 1125) the message from output. The message delayperiod may be determined by various factors, including, the mediationtemperature, message frequency, and/or the amount the message scoreexceeded a message score threshold. For example, if several messages aresent in high frequency, the delay may be longer compared to messagessent in low frequency. In some embodiments, UEs 705 may display thedelay period before sending the message.

Process 1100 may further include outputting (at 1130) the message to UEs705 (e.g., UEs 705 associated with sending participant, receivingparticipant(s) and/or mediator(s)). In some embodiments, process 1100may output the message in any data format such as short message service,multimedia messaging service, internet protocol-based messaging and/orother text-based messaging architecture. The message may be sent overnetwork 710. In some embodiments, the receiving participant may bequeried (e.g., through a notification or display on UE 705) regardingwhether the receiving participant perceives the message as suitable(e.g., on a scale of more to less suitable, etc.). The query may beinitiated by a participant (e.g., voluntarily by the receivingparticipant or mandated by the sending participant) or by one or moredevices (e.g., IMMS 715). This query may provide feedback to establishuser-reinforced machine learning for reference language repository 725and/or other data structures.

FIG. 12 illustrates a process 1200 for remedying a message by rejectingthe message. In some embodiments, some or all of process 1200 may beperformed by IMMS 715 and/or by one or more other devices or systems. Asdiscussed above, process 1200 may be favored, for example, in instanceswhen a message score exceedingly surpasses the message score threshold.Process 1200 is demonstrated, for example, in FIG. 3 and FIG. 6.

As shown, process 1200 may include receiving (at 1205) a message forrejection. As discussed above, process 900 (e.g., at 945) may determineto modify a message if the message score exceeds a message scorethreshold (e.g., at 935).

Process 1200 may include outputting (at 1210) a rejection message to thesending participant. The rejection message may indicate the reason whythe message was not sent to the receiving participant (e.g., asdemonstrated in messages 305 and 605).

Process 1200 may further embody outputting (at 1215) the receivedmessage (e.g., from 1205) to mediator UE 705. This provides theopportunity for the mediator participant to monitor and observe theprogression of the mediation. In such instances (e.g., for example, asexemplified in FIG. 6, message 605), process 1200 may suggest to thesending participant that the mediator participant take a more involvedrole in the mediation. In some embodiments, future messages from thesending participant may be submitted to the mediator for approval. Forexample, IMMS 715 may receive a message for rejection and not providethe message to UE 705 associated with a mediator (e.g., 705-1) but notto UE 705 associated with a receiving participant. This may allow forthe mediator participant to advise the sending participant with moreknowledge than what is otherwise visible in the mediation exchange(e.g., the mediator will be able to see rejected messages whenattempting to advise a mediation participant).

In some embodiments, process 1200 may output (at 1215) the message inany data format such as short message service, multimedia messagingservice, internet protocol-based messaging and/or other text-basedmessaging architecture. The message may be output through network 710.

Process 1200 may further include requesting (at 1220) a new message fromthe sending participant. As demonstrated, for example, in FIG. 3 (e.g.,at message 305), this may occur in the original rejection message output(e.g., at 1210) to the sending participant.

Process 1200 may additionally include receiving (at 1225) a new messagefrom the sending participant. In some embodiments, process 1200 mayreceive the message in any data format such as short message service,multimedia messaging service, internet protocol-based messaging and/orother text-based messaging architecture. The message may be receivedthrough network 710.

Process 1200 may include outputting (at 1230) the new received message(e.g., from 1225) to process 900. In some embodiments, process 1200 mayoutput the new received message in any data format such as short messageservice, multimedia messaging service, internet protocol-based messagingand/or other text-based messaging architecture. The message may betransmitted over network 710.

FIG. 13 illustrates example components of device 1300. One or more ofthe devices described above may include one or more devices 1300. Device1300 may include bus 1310, processor 1320, memory 1330, input component1340, output component 1350, and communication interface 1360. Inanother implementation, device 1300 may include additional, fewer,different, or differently arranged components.

Bus 1310 may include one or more communication paths that permitcommunication among the components of device 1300. Processor 1320 mayinclude a processor, microprocessor, or processing logic that mayinterpret and execute instructions. Memory 1330 may include any type ofdynamic storage device that may store information and instructions forexecution by processor 1320, and/or any type of non-volatile storagedevice that may store information for use by processor 1320.

Input component 1340 may include a mechanism that permits an operator toinput information to device 1300, such as a keyboard, a keypad, abutton, a switch, etc. Output component 1350 may include a mechanismthat outputs information to the operator, such as a display, a speaker,one or more light emitting diodes (“LEDs”), etc.

Communication interface 1360 may include any transceiver-like mechanismthat enables device 1300 to communicate with other devices and/orsystems. For example, communication interface 1360 may include anEthernet interface, an optical interface, a coaxial interface, or thelike. Communication interface 1360 may include a wireless communicationdevice, such as an infrared (“IR”) receiver, a Bluetooth® radio, or thelike. The wireless communication device may be coupled to an externaldevice, such as a remote control, a wireless keyboard, a mobiletelephone, etc. In some embodiments, device 1300 may include more thanone communication interface 1360. For instance, device 1300 may includean optical interface and an Ethernet interface.

Device 1300 may perform certain operations relating to one or moreprocesses described above. Device 1300 may perform these operations inresponse to processor 1320 executing software instructions stored in acomputer-readable medium, such as memory 1330. A computer-readablemedium may be defined as a non-transitory memory device. A memory devicemay include space within a single physical memory device or spreadacross multiple physical memory devices. The software instructions maybe read into memory 1330 from another computer-readable medium or fromanother device. The software instructions stored in memory 1330 maycause processor 1320 to perform processes described herein.Alternatively, hardwired circuitry may be used in place of or incombination with software instructions to implement processes describedherein. Thus, implementations described herein are not limited to anyspecific combination of hardware circuitry and software.

The foregoing description of implementations provides illustration anddescription, but is not intended to be exhaustive or to limit thepossible implementations to the precise form disclosed. Modificationsand variations are possible in light of the above disclosure or may beacquired from practice of the implementations.

For example, while series of blocks and/or signals have been describedwith regard to FIGS. 8 through 12, the order of the blocks and/orsignals may be modified in other implementations. Further, non-dependentblocks and/or signals may be performed in parallel. Additionally, whilethe figures have been described in the context of particular devicesperforming particular acts, in practice, one or more other devices mayperform some or all of these acts in lieu of, or in addition to, theabove-mentioned devices.

The actual software code or specialized control hardware used toimplement an embodiment is not limiting of the embodiment. Thus, theoperation and behavior of the embodiment has been described withoutreference to the specific software code, it being understood thatsoftware and control hardware may be designed based on the descriptionherein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of the possible implementations. Infact, many of these features may be combined in ways not specificallyrecited in the claims and/or disclosed in the specification. Althougheach dependent claim listed below may directly depend on only one otherclaim, the disclosure of the possible implementations includes eachdependent claim in combination with every other claim in the claim set.

Further, while certain connections or devices are shown, in practice,additional, fewer, or different, connections or devices may be used.Furthermore, while various devices and networks are shown separately, inpractice, the functionality of multiple devices may be performed by asingle device, or the functionality of one device may be performed bymultiple devices. Further, multiple ones of the illustrated networks maybe included in a single network, or a particular network may includemultiple networks. Further, while some devices are shown ascommunicating with a network, some such devices may be incorporated, inwhole or in part, as a part of the network.

Some implementations are described herein in conjunction withthresholds. To the extent that the term “exceeds” (or similar terms) isused herein to describe a relationship of a value to a threshold, it isto be understood that the term “greater than or equal to” (or similarterms) could be similarly contemplated, even if not explicitly stated.Similarly, to the extent that the term “less than” (or similar terms) isused herein to describe a relationship of a value to a threshold, it isto be understood that the term “less than or equal to” (or similarterms) could be similarly contemplated, even if not explicitly stated.

To the extent the aforementioned implementations collect, store, oremploy personal information provided by individuals, it should beunderstood that such information shall be collected, stored, and used inaccordance with all applicable laws concerning protection of personalinformation. Additionally, the collection, storage, and use of suchinformation may be subject to consent of the individual to such activity(for example, through “opt-in” or “opt-out” processes, as may beappropriate for the situation and type of information). Storage and useof personal information may be in an appropriately secure mannerreflective of the type of information, for example, through variousencryption and anonymization techniques for particularly sensitiveinformation.

No element, act, or instruction used in the present application shouldbe construed as critical or essential unless explicitly described assuch. An instance of the use of the term “and,” as used herein, does notnecessarily preclude the interpretation that the phrase “and/or” wasintended in that instance. Similarly, an instance of the use of the term“or,” as used herein, does not necessarily preclude the interpretationthat the phrase “and/or” was intended in that instance. Also, as usedherein, the article “a” is intended to include one or more items, andmay be used interchangeably with the phrase “one or more.” Where onlyone item is intended, the terms “one,” “single,” “only,” or similarlanguage is used. Further, the phrase “based on” is intended to mean“based, at least in part, on” unless explicitly stated otherwise.

1. A device, comprising: a non-transitory computer-readable mediumstoring a set of processor-executable instructions; and one or moreprocessors configured to execute the set of processor-executableinstructions, wherein executing the set of processor-executableinstructions causes the one or more processors to: receive a messageinput at a user equipment (“UE”), the message being associated with arecipient UE; utilize natural language processing to determine an intentof the message; generate a score for the message based on the intent ofthe message; determine that the score exceeds one or more thresholdscores, out of a plurality of threshold scores; identify, based on thenatural language processing, that the message includes an ambiguousphrase; output, to the UE, an indication of the identified ambiguousphrase; receive, from the UE and based on the indication of theidentified ambiguous phrase, a first alternate phrase; identify, basedon the first alternate phrase and further based on the score for themessage, a second alternate phrase; select a remedial measure, out of aplurality of candidate remedial measures, to perform on the messagebased on the determined threshold scores exceeded by the generated scoreof the message and further based on the identification of the ambiguousphrase; and perform the selected remedial measure on the message,wherein performing the selected remedial measure includes: modifying themessage by replacing, in the message and prior to the message beingforwarded to the recipient UE, the identified ambiguous phrase with theidentified second alternate phrase; and outputting the modified messageto the recipient UE.
 2. The device of claim 1, wherein generating thescore for the message further includes: comparing segments of phrasesand/or words in the message, as input at the UE, to a data repositorycontaining phrases and/or words.
 3. The device of claim 1, whereinexecuting the processor-executable instructions further causes the oneor more processors to: determine a temperature level based on anassociation between the UE and the recipient UE.
 4. The device of claim3, wherein executing the processor-executable instructions furthercauses the one or more processors to: determine the one or morethreshold scores based on the determined temperature level. 5.(canceled)
 6. The device of claim 1, wherein executing theprocessor-executable instructions further causes the one or moreprocessors to: associate the each of the determined plurality of messagescore thresholds with the each of the plurality of candidate remedialmeasures.
 7. The device of claim 1, wherein outputting the modifiedmessage includes outputting the modified message via a network to therecipient UE.
 8. The device of claim 1, wherein the selected remedialmeasure is a first remedial measure, wherein executing theprocessor-executable instructions further causes the one or moreprocessors to: after performing the first remedial measure, generate anew score for the message based on the intent of the message; determinethat the new score exceeds one or more threshold scores, out of aplurality of threshold scores; select a second remedial measure, out ofa plurality of candidate remedial measures, to perform on the messagebased on which threshold scores are exceeded by the generated new scoreof the message; and perform the selected second remedial measure on themessage.
 9. The device of claim 1, wherein executing theprocessor-executable instructions further causes the one or moreprocessors to: identify information regarding a plurality of phrases orwords in the received message input at the UE, the informationincluding, for a particular phrase or word, of the plurality of phrasesor words, at least one of: an intent of a particular phrase or word, ascore for the phrase and/or word, or alternative phrases or words forthe particular phrase or word, wherein generating the score includesgenerating the score based on the information regarding the plurality ofphrases or words in the received message.
 10. A non-transitorycomputer-readable medium, storing a set of processor-executableinstructions, which, when executed by one or more processors, cause theone or more processors to: receive a message input at a user equipment(“UE”), the message being associated with a recipient UE; utilizenatural language processing to determine an intent of the message;generate a score for the message based on the intent of the message;determine that the score exceeds one or more threshold scores, out of aplurality of threshold scores; identify, based on the natural languageprocessing, that the message includes an ambiguous phrase; output, tothe UE, an indication of the identified ambiguous phrase; receive, fromthe UE and based on the indication of the identified ambiguous phrase, afirst alternate phrase; identify, based on the first alternate phraseand further based on the score for the message, a second alternatephrase; select a remedial measure, out of a plurality of candidateremedial measures, to perform on the message based on the determinedthreshold scores exceeded by the generated score of the message andfurther based on the identification of the ambiguous phrase; and performthe selected remedial measure on the message, wherein performing theselected remedial measure includes: modifying the message by replacing,in the message and prior to the message being forwarded to the recipientUE, the identified ambiguous phrase with the identified second alternatephrase; and outputting the modified message to the recipient UE.
 11. Thenon-transitory computer-readable medium of claim 10, wherein generatingthe score for the message further includes: comparing segments ofphrases and/or words in the message, as input at the UE, to a datarepository containing phrases and/or words.
 12. The non-transitorycomputer-readable medium of claim 10, wherein execution of theprocessor-executable instructions further causes the one or moreprocessors to: determine a temperature level based on an associationbetween the UE and the recipient UE.
 13. The non-transitorycomputer-readable medium of claim 12, wherein execution of theprocessor-executable instructions further causes the one or moreprocessors to: determine the one or more threshold scores based on thedetermined temperature level.
 14. (canceled)
 15. The non-transitorycomputer-readable medium of claim 10, wherein execution of theprocessor-executable instructions further causes the one or moreprocessors to: after performing the first remedial measure, generate anew score for the message based on the intent of the message; determinethat the new score exceeds one or more threshold scores, out of aplurality of threshold scores; select a second remedial measure, out ofa plurality of candidate remedial measures, to perform on the messagebased on which threshold scores are exceeded by the generated score ofthe message; and perform the selected second remedial measure on themessage.
 16. A method, comprising: receiving a message input at a userequipment (“UE”), the message being associated with a recipient UE;utilizing natural language processing to determine an intent of themessage; generating a score for the message based on the intent of themessage; determining that the score exceeds one or more thresholdscores, out of a plurality of threshold scores; identifying, based onthe natural language processing, that the message includes an ambiguousphrase; outputting, to the UE, an indication of the identified ambiguousphrase; receiving, from the UE and based on the indication of theidentified ambiguous phrase, a first alternate phrase; identifying,based on the first alternate phrase and further based on the score forthe message, a second alternate phrase; selecting a remedial measure,out of a plurality of candidate remedial measures, to perform on themessage based on the determined threshold scores exceeded by thegenerated score of the message and further based on the identificationof the ambiguous phrase; and performing the selected remedial measure onthe message, wherein performing the selected remedial measure includes:modifying the message by replacing, in the message and prior to themessage being forwarded to the recipient UE, the identified ambiguousphrase with the identified second alternate phrase; and outputting themodified message to the recipient UE.
 17. The method of claim 16,wherein generating the score for the message further comprises:comparing segments of phrases and/or words in the message, as input atthe UE, to a data repository containing phrases and/or words.
 18. Themethod of claim 16, further comprising: determining a temperature levelbased on an association between the UE and the recipient UE.
 19. Themethod of claim 18, further comprising: determining the one or morethreshold scores based on the determined temperature level.
 20. Themethod of claim 16, further comprising: identifying informationregarding a plurality of phrases or words in the receive message inputat the UE, the information including, for a particular phrase or word,of the plurality of phrases or words, at least one of: an intent of aparticular phrase or word, a score for the phrase and/or word, oralternative phrases or words for the particular phrase or word, whereingenerating the score includes generating the score based on theinformation regarding the plurality of phrases or words with in thereceived message.
 21. The method of claim 16, wherein the message is afirst message, wherein performing the selected remedial measure furtherincludes: presenting, in a same user interface at the UE via which themessage was input, a prompt requesting indicating the modified message;receiving, via the same user interface at the UE, a second message inresponse to the prompt, wherein outputting the modified message isperformed based on receiving the second message, wherein the secondmessage is not sent to the recipient UE.
 22. The device of claim 1,wherein the message is a first message, wherein performing the selectedremedial measure further includes: presenting, in a same user interfaceat the UE via which the message was input, a prompt requestingindicating the modified message; receiving, via the same user interfaceat the UE, a second message in response to the prompt, whereinoutputting the modified message is performed based on receiving thesecond message, wherein the second message is not sent to the recipientUE.